Head of Compute

Responsibilities

• Own the economics of compute end-to-end: the unit economics of every contract, the margin architecture across training and inference products, the long-term P&L consequences of today's supply bets
• Partner with Finance and leadership on capital strategy — how much to commit, to whom, for how long, on which hardware, with what balance sheet exposure
• Build the frameworks that turn supply decisions into clear financial outcomes, and that let us make multi-hundred-million-dollar bets with conviction under uncertainty
• Shape the commercial architecture of the open compute ecosystem: how committed capacity, spot markets, credit structures, and partner economics fit together
• Sourcing & Contracting
• Own end-to-end procurement of GPU capacity globally — across hyperscalers, tier-one neoclouds, regional operators, and emerging providers in North America, Europe, the Middle East, and Asia
• Negotiate and close reserved capacity agreements, spot and burst arrangements, MSAs, DPAs, and order forms at nine- and ten-figure scale
• Secure early access to the latest generations of accelerators (B200, GB200, and what comes next) — in the quantities we need, before our competitors
• Build and maintain the senior relationships that make Prime Intellect the partner of choice for providers deciding where to allocate scarce capacity
• Co-Design with Research & Engineering
• Work closely with our research team to translate training roadmaps, RL workloads, and open model ambitions into concrete compute requirements — and back the other way, to surface what's possible given the supply we can secure
• Partner with Engineering on acceptance testing, goodput validation, and the technical qualification of new providers and hardware
• Sit at the table where the biggest calls get made: which open models we train, which customers we serve, which bets are worth the capital
• Market Intelligence & Positioning
• Track pricing, availability, and provider dynamics continuously across every major global market
• Serve as the internal source of truth on the compute market — who's credible, who's mispriced, where supply is about to tighten, which providers will still exist in 18 months, where the next wave of capacity is coming online
• Advisory leadership on the strategic bets that define the company: which accelerators, which providers, which geographies, which contract structures, which moments to lean in hard

Qualifications

• Strong business and financial instincts — you think natively in unit economics, margin structure, and capital allocation, and you can model the long-term P&L consequences of complex supply decisions
• Deep fluency in the global AI compute market: you know the providers, the hardware generations and their real tradeoffs, the pricing dynamics, and where the market is going over the next 12–24 months
• Enough technical understanding to be dangerous — you can push back on a vendor's spec sheet, read a cluster topology diagram, understand why two nominally identical clusters deliver different goodput, and have a real conversation with researchers about what their workloads need
• Serious commercial chops: you've negotiated and closed contracts at meaningful scale, know how to find and use leverage, and understand how deal structure drives downstream economics
• Comfortable operating at the intersection of finance, commercial, product, and engineering — and translating fluently between all of them
• High ownership: you see gaps and build the fix before anyone asks
• AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster